The two massive open online courses focus on growing knowledge in reinforcement learning and in the application of machine learning

EDMONTON, AB (December 2, 2020) – Two online Specializations presented by the University of Alberta and the Alberta Machine Intelligence Institute (Amii) have reached more than 110,000 enrolments since first launching in August 2019. The massive open online courses (MOOCs), produced in partnership with Coursera, seek to grow knowledge and skills in artificial intelligence (AI) and machine learning to prepare learners for future careers in the field. Both Specializations are currently accepting enrolment; learn more at https://www.coursera.org/specializations/reinforcement-learning and https://www.coursera.org/specializations/machine-learning-algorithms-real-world.

The Reinforcement Learning Specialization was developed and instructed by a team from the University of Alberta led by Martha White, an Associate Professor in the Department of Computing Science and a Fellow and Canada CIFAR AI Chair at Amii, and Adam White, an Assistant Professor of Computing Science and a Fellow and Canada CIFAR AI Chair at Amii. Meanwhile, the Specialization on Machine Learning: Algorithms in the Real World was produced by Amii and instructed by Anna Koop, Managing Director of Applied Science, who is also an alumnae of the University of Alberta.

"We are pleased to offer the Reinforcement Learning specialization, helping new learners and life-long learners around the world stay current with the rapid innovations in computing science. Closer to home, MOOCs from our Department of Computing Science offer accessible retooling options for a data driven workforce across economic sectors. Artificial Intelligence, machine learning, and reinforcement learning are areas of expertise in the University of Alberta's Faculty of Science, and we are home to world leaders in this field, including Rich Sutton, Adam White, and Martha White, who are all featured in these courses. We are delighted that their expertise is being accessed and leveraged worldwide, and in Alberta," says Matina Kalcounis-Rueppell, dean in the University of Alberta's Faculty of Science.

“Amii exists to inspire world-changing machine intelligence and to empower companies to grow their in-house AI and machine learning capabilities. These specializations help learners from around the world connect into our world-leading expertise and empower Albertans to grow their own knowledge and skills in AI to unlock opportunities for their businesses and future careers. In AI, talent is key, and once again, Amii and the University of Alberta are demonstrating our key role in producing some of the world’s most skilled individuals,” says Cam Linke, CEO of Amii.

Reinforcement Learning

Reinforcement learning is a branch of machine learning that enables AI systems to learn through experience. Reinforcement Learning systems interact with their environments, often through trial and error, earning positive or negative rewards based on their actions. Humans define the overall task and relevant rewards that the system uses to discover the best action to take in a given situation. Instead of being told what actions to take to achieve a goal, the system must learn which actions yield the most reward by trying them. Over time, the system develops a policy (or way of acting) that lets it select the action that will best achieve the goal, which can help us discover the optimal actions to take in a given scenario.

Reinforcement learning has applications in process optimization and improvement, as part of a recommender or intelligent tutoring system, and for adaptive control and decision making in autonomous systems.

Through the Specialization, learners gain understanding of the foundations of much of modern probabilistic AI and are prepared to take more advanced courses, or to apply AI tools and ideas to real-world problems. This content focuses on "small-scale" problems in order to understand the foundations of Reinforcement Learning. The course finishes with a capstone project to implement a complete reinforcement learning solution to a specific problem.

“We’re pleased to have reached so many with our specialization,” says Martha White. “Reinforcement Learning is the future of AI, with applications across all sectors of our society. We’re excited to bring these concepts to a global audience of learners and help them use these techniques in the real world.”

Machine Learning: Algorithms in the Real World

Machine Learning: Algorithms in the Real World focuses on applied knowledge in AI and machine learning. The specialization is designed for professionals of varying skill levels who want to learn the fundamentals of applying machine learning to data analysis and automation. After completing all four courses, learners are able to clearly define a machine learning problem, identify appropriate data, train a classification algorithm, improve results, and deploy in the real world.

With a world-wide shortage of AI talent, the course is just one way that Amii leverages scientific excellence from institutions like the University of Alberta in order to accelerate AI adoption in industry.

“Artificial intelligence and machine learning are powerful technologies that are shaping our world across industries and sectors,” says Anna Koop. “There are almost limitless possibilities for businesses to apply AI to achieve their goals, and we want to ensure businesses and individuals understand these technologies and the competitive advantages they can provide. There is so much potential for good, and our specialization is a great first step for anyone looking to grow their knowledge.”

Together, these two Specializations leverage the long-standing excellence in artificial intelligence and machine learning of both the University of Alberta and Amii. They provide a means for local and international learners alike to gain access to the world-leading research, knowledge and talent being developed in Alberta.

More Information

What is artificial intelligence?

Artificial intelligence is a discipline of computing science that allows a system to complete tasks we typically associate with cognitive functions – such as reasoning, strategizing and problem-solving – without requiring an explicit solution for every variation.

Why focus on machine learning?

Machine learning is a set of computational techniques that use data to create models that make predictions about future data. These models independently learn and continuously adapt to changing environments without being explicitly programmed for the data they encounter. Machine learning is a crucial component in many artificial intelligence systems.

Industry is particularly interested in adopting applied machine learning, and investing in advanced research in the field, because of the focus on using historical data to inform future opportunities for systems improvement, discoveries, and augmenting human-cognitive capacity.

About the University of Alberta

The University of Alberta in Edmonton is one of Canada's top teaching and research universities, with an international reputation for excellence across the humanities, sciences, creative arts, business, engineering and health sciences. Our artificial intelligence research is ranked 2nd in the US and Canada, according to the metrics-based system, CSRankings.

About Amii

One of Canada’s three centres of AI excellence as part of the Pan-Canadian AI Strategy, Amii (the Alberta Machine Intelligence Institute) is an Alberta-based non-profit institute that supports world-leading research in artificial intelligence and machine learning and translates scientific advancement into industry adoption. Amii grows AI capabilities through advancing leading-edge research, delivering exceptional educational offerings and providing business advice – all with the goal of building in-house AI capabilities. For more information, visit amii.ca.